Solving Network Coding Resource Problem Using Ant Colony Optimization
Jingyi Li · 2018
The limit of multicast throughput of traditional routing is broken by network coding operations when we transfer data information in the communication networks. However, if we assume every node performs network coding in the network, the efficiency of the whole data transfer process will be greatly influenced, e.g. the buffering resource will be heavily occupied. We present Ant Colony Optimization to minimize the coding operations while guarantying the required data multicast rate. It is featured with pheromone and heuristic information update scheme to exploit local and global information. The network graph is decomposed into a more complex graph with all coding possible nodes to function separately without coding for simulation. Ant groups are used to explore multiple path sets on the decomposed graph. We introduce Ant Colony Optimization together with Genetic Algorithm and discuss the probability and performance of Ant Colony Optimization to solve this problem. The paper ends with main conclusions and recommendations for further study of network coding resource minimization problem.